Traditional molecular modeling is performed at atomic resolution, which relies on X-ray and NMR experiments to provide structural information. When dealing with biomolecular assemblies of millions of atoms, atomic description of molecular objects becomes very computational inefficient. We developed a method that uses map objects for molecular modeling to efficiently derive structural information from experimental maps, as well as conveniently manipulate map objects, perform conformational search directly using map objects. This development work has been implemented into CHARMM as the EMAP module. This implementation enables CHARMM to manipulate map objects, including map input, output, comparison, docking, etc. Other experiment such as transition metal ion FRET (tmFRET) is becoming a useful way to obtain protein structure information. A new focus of our research is to combine efficient simulation technique with structural information from experiment to assist high throughput protein structure determination. High resolution Structure determination from EM maps The advent of direct electron detectors has enabled the routine use of single-particle cryo-electron microscopy (EM) approaches to determine structures of a variety of protein complexes at near-atomic resolution. Here, we report the development of methods to account for local variations in defocus and beam-induced drift, and the implementation of a data-driven dose compensation scheme that significantly improves the extraction of high-resolution information recorded during exposure of the specimen to the electron beam. These advances enable determination of a cryo-EM density map for -galactosidase bound to the inhibitor phenylethyl -D-thiogalactopyranoside where the ordered regions are resolved at a level of detail seen in X-ray maps at 1.5 resolution. Using this density map in conjunction with constrained molecular dynamics simulations provides a measure of the local flexibility of the non-covalently bound inhibitor and offers further opportunities for structure-guided inhibitor design. Structure mechanism of Glutamate receptor activation Ionotropic glutamate receptors are cation channels that mediate signal transmission by depolarizing the postsynapitic membrane in response to L-glutamate release from the presynaptic neuron. Within the iGluR family of receptors are a-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPA), kainite(KA), and N-methyl-D-aspartate (NMDA) subtypes, receptors that are all activated by glutamate and related in amino acid sequence, yet distinct in overall architecture, pharmacology, and biophysical characteristics. AMPA receptors are tetrameric complexes composed of subunits with a modular domain arrangement, beginning with the amino-terminal domain(ATD), the ligand- or agonist-binding domain (LBD), and the pore-forming transmembrane domain (TMD). Because AMPA receptors undergo rapid and nearly complete desensitization in the continued presence of agonist, it has proven difficult to elucidate high-resolution structures of agonist-bound, activated states and to define mechanism by which the chemical potential of agonist binding is transduced into the mechanical force of ion channel gating. The map-restrained self-guided Langevin dynamics (MapSGLD) simulation method we developed previously can utilize structural information embedded in a force field to flexibly fit macromolecular systems into low resolution maps to obtain energetically favored atomic structures that satisfy the maps. We perform flexible fitting with MapSGLD to obtain atomic structures of the glutamate receptor from EM maps. The open state atomic structure of the glutamate receptor shows the LBD in the clamshell closed conformation that agrees with the LBD x-ray structure. In addition to structural determination, MapSGLD provides dynamic information about the transition between different states. Protein-protein docking using map objects Protein-protein docking is a molecular modeling strategy to predict biomolecular complexes and assemblies. Traditional protein-protein docking is performed at atomic resolution, which relies on X-ray and NMR experiments to provide structural information. When deal with biomolecular assemblies of millions of atoms, atomic description of molecular objects becomes very computational inefficient. This article describes a development work that introduces map objects to molecular modeling studies to efficiently derive complex structures through map-map conformational search. This method has been implemented into CHARMM as the EMAP command and into AMBER in its SANDER program. This development enables molecular modeling and simulation to manipulate map objects, including map input, output, comparison, docking, etc. Through map objects, users can efficiently construct complex structures through protein-protein docking as well as from electron microscopy maps according to low map energies. Using a T-cell receptor variable domain and Acetylcholine Binding Protein (ACHBP) as example systems, we showed the application to model an energetic optimized complex structure according to a complex map. The map objects serves as a bridge between high resolution atomic structures and low resolution image data.